Solar+Storage/Method and Modeling Assumptions

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Methods and Modeling Assumptions

<a href="#locations-modeled">Locations Modeled</a> | <a href="#utility-rates-modeled">Utility Rates Modeled</a> | <a href="#building-types-load-profiles-modeled">Building Types and Load Profiles Modeled</a> | <a href="#technology-cost-assumptions">Technology Cost Assumptions</a> | <a href="#policies-finance-assumptions">Policies and Finance Assumptions</a> | <a href="#hardware-assumptions">Hardware Assumptions</a> | <a href="#reopt-model">REopt Model</a>

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Locations Modeled

Commercial buildings were modeled for 16 locations, representing every climate zone across the U.S.

Annual Load Factor for Building Types Modeled (average acros all locations)

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Utility Rates Modeled

Commercial utility rates were selected for the utility with the largest commercial customer base within each climate zone. Rates and building types were matched, based on the load profile of the building and the eligibility requirements stated in the utility’s rate tariff sheet.

The modeling included a variety of tariffs. Some have demand charge elements, some have time-of-use elements, some have both time-of-use and demand elements, and a few were flat rates. All of the tariffs were taken from NREL’s Utility Rate Database and were up to date as of January 2017.

Annual Load Factor for Building Types Modeled (average acros all locations)

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Building Types and Load Profiles Modeled

Hourly load profiles were generated for the 16 Department of Energy Commercial Reference Buildings (1980’s stock). Different profiles were created for each ASHRAE climate zone (see map below). These annual, hourly load profiles were used as inputs into the optimization model. You can explore the load profiles using the interactive chart, below.

Building Types and Load Profiles Modeled

(Read more about this map here)

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Technology Cost Assumptions

Optimization modeling was conducted for seven solar photovoltaic and battery storage price points, representing anticipated cost trajectories.

Cost Point A represents conservative technology costs in the current market. Some stakeholders are reporting current costs closer to Cost Points B and C.

Cost Point G represents estimated technology costs by 2037.

The solar technology cost trajectory is based on NREL’s Annual Technology Baseline. Battery storage costs are based on NREL discussions with a variety of battery suppliers and developers.

Solar and Battery Storage Cost Assumptions used for Optimization Modeling

Components included in the Cost Assumptions

Battery & Hardware Costs
Inverter - power conversion
Container or housing
Container extras (insulation/walls)
Electrical conduit (inside of container)
Communication device
Meter (revenue grade)
Fire detection
Fire suppression
AC main panel
DC disconnect
Isolation transformer
AUX power - lighting etc.

Soft Costs
Developer cost (customer acquisition)

Engineering, Planning & Construction Costs
Control system/SCADA
Site preparation
Loading & drive from OEM site
Lifting & hoisting by crane on site
PE stamped calcs & drawings
OEM testing and commissioning
Electrical BOS outside of container (conduit, wiring, DC cable)
Electrical labor
Structural BOS (fencing)
EPC overhead & profit

Policy & Financing Assumptions

Unless otherwise noted:
System life20 years.
Inflation Rate2.5%
Discount Rate10.2%
Net metering is not included. When included, system size is capped at 100% load.
30% Investment Tax Credit is included.
"Modified Accelerated Capital Depreciation (MACRS):5 year + bonus depreciation for solar and battery system components (if battery charged >25% from grid, 7 year depreciation).
No other state or federal incentives are included.

Hardware Assumptions

Inverter & Storage ReplacementIn Year 10
Total Round Trip Efficiency82.9%
Battery Throughput85%
Inverter Efficiency92%
Rectifier Efficiency90%
Minimum Charge20%
Initial State of Charge50%

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The REopt Model

The Renewable Energy Optimization Model (REopt) provides cost-optimal technology solutions at a single site, or across a portfolio of sites.

REopt is a mixed integer linear program that outputs optimal technology sizing and hourly dispatch strategies, along with financial data.

REopt can identify optimal system sizes, given other parameters, or can output financial data for set system sizes. Multiple on-site technologies, including existing diesel generators, can be considered in the optimization.

The REopt model is currently run by NREL analysts, in-house. A web-based version of the tool is currently in development, and expected to be released as a beta-version in September 2017.

For more information about REopt, visit: